update the image in the samples to use the new component images

[gaoning777]

This change is 

[gaoning777]

/test kubeflow-pipeline-e2e-test

[gaoning777]

/test kubeflow-pipeline-sample-test

[Ark-kun]

I think we can do it much easier, cleaner and less fragile:

dsl-compile --py taxi-cab-classification-pipeline.py --output taxi-cab-classification-pipeline.yaml

sed -i -e "s|gcr.io/ml-pipeline/ml-pipeline-dataflow-tfdv:\([a-zA-Z0-9_.-]\)\+|${DATAFLOW_TFDV_IMAGE}|g" taxi-cab-classification-pipeline.yaml

[gaoning777]

The approach you mentioned also requires changes to the run_tfx_test.py such that it accepts yaml files.
I think it does not make much difference whether updating the image tag in the source code or the compiled yaml.

[Ark-kun]

The code is extremely fragile. Even removing a single space will break it.

[gaoning777]

Make sense.
Fixed.

[Ark-kun]

Make sense.
Fixed.

Thanks.

[Ark-kun]

Don't you also need to update the kubeflow-training-classification test?

[gaoning777]

I found out that the client handles all the different pipeline formats.

[Ark-kun]

Don't you also need to update the kubeflow-training-classification test?

I meant this part for example:

pipelines/test/sample-test/run_test.sh

Line 156 in 84b071c

dsl-compile --py kubeflow-training-classification.py --output kubeflow-training-classification.zip

[gaoning777]

postsubmit test is not testing the tf-training sample. So, only the tfx and xgboost is updated.

[Ark-kun]

postsubmit test is not testing the tf-training sample. So, only the tfx and xgboost is updated.

I see.

/lgtm

[gaoning777]

/approve

[k8s-ci-robot]

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[k8s-ci-robot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: gaoning777

The full list of commands accepted by this bot can be found here.

The pull request process is described here

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• test/OWNERS [gaoning777]

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